Bidirectional modulation of TCA cycle metabolites and anaplerosis by metformin and its combination with SGLT2i.

BACKGROUND: Metformin and sodium-glucose-cotransporter-2 inhibitors (SGLT2i) are cornerstone therapies for managing hyperglycemia in diabetes. However, their detailed impacts on metabolic processes, particularly within the citric acid (TCA) cycle and its anaplerotic pathways, remain unclear. This study investigates the tissue-specific metabolic effects of metformin, both as a monotherapy and in combination with SGLT2i, on the TCA cycle and associated anaplerotic reactions in both mice and humans. METHODS: Metformin-specific metabolic changes were initially identified by comparing metformin-treated diabetic mice (MET) with vehicle-treated db/db mice (VG). These findings were then assessed in two human cohorts (KORA and QBB) and a longitudinal KORA study of metformin-naïve patients with Type 2 Diabetes (T2D). We also compared MET with db/db mice on combination therapy (SGLT2i + MET). Metabolic profiling analyzed 716 metabolites from plasma, liver, and kidney tissues post-treatment, using linear regression and Bonferroni correction for statistical analysis, complemented by pathway analyses to explore the pathophysiological implications. RESULTS: Metformin monotherapy significantly upregulated TCA cycle intermediates such as malate, fumarate, and α-ketoglutarate (α-KG) in plasma, and anaplerotic substrates including hepatic glutamate and renal 2-hydroxyglutarate (2-HG) in diabetic mice. Downregulated hepatic taurine was also observed. The addition of SGLT2i, however, reversed these effects, such as downregulating circulating malate and α-KG, and hepatic glutamate and renal 2-HG, but upregulated hepatic taurine. In human T2D patients on metformin therapy, significant systemic alterations in metabolites were observed, including increased malate but decreased citrulline. The bidirectional modulation of TCA cycle intermediates in mice influenced key anaplerotic pathways linked to glutaminolysis, tumorigenesis, immune regulation, and antioxidative responses. CONCLUSION: This study elucidates the specific metabolic consequences of metformin and SGLT2i on the TCA cycle, reflecting potential impacts on the immune system. Metformin shows promise for its anti-inflammatory properties, while the addition of SGLT2i may provide liver protection in conditions like metabolic dysfunction-associated steatotic liver disease (MASLD). These observations underscore the importance of personalized treatment strategies.

Cysteine induces mitochondrial reductive stress in glioblastoma through hydrogen peroxide production.

Glucose and amino acid metabolism are critical for glioblastoma (GBM) growth, but little is known about the specific metabolic alterations in GBM that are targetable with FDA-approved compounds. To investigate tumor metabolism signatures unique to GBM, we interrogated The Cancer Genome Atlas for alterations in glucose and amino acid signatures in GBM relative to other human cancers and found that GBM exhibits the highest levels of cysteine and methionine pathway gene expression of 32 human cancers. Treatment of patient-derived GBM cells with the FDA-approved single cysteine compound N-acetylcysteine (NAC) reduced GBM cell growth and mitochondrial oxygen consumption, which was worsened by glucose starvation. Normal brain cells and other cancer cells showed no response to NAC. Mechanistic experiments revealed that cysteine compounds induce rapid mitochondrial H2O2 production and reductive stress in GBM cells, an effect blocked by oxidized glutathione, thioredoxin, and redox enzyme overexpression. From analysis of the clinical proteomic tumor analysis consortium (CPTAC) database, we found that GBM cells exhibit lower expression of mitochondrial redox enzymes than four other cancers whose proteomic data are available in CPTAC. Knockdown of mitochondrial thioredoxin-2 in lung cancer cells induced NAC susceptibility, indicating the importance of mitochondrial redox enzyme expression in mitigating reductive stress. Intraperitoneal treatment of mice bearing orthotopic GBM xenografts with a two-cysteine peptide induced H2O2 in brain tumors in vivo. These findings indicate that GBM is uniquely susceptible to NAC-driven reductive stress and could synergize with glucose-lowering treatments for GBM.

Breast adipose tissue-derived extracellular vesicles from obese women alter tumor cell metabolism.

Breast adipose tissue is an important contributor to the obesity-breast cancer link. Extracellular vesicles (EVs) are nanosized particles containing selective cargo, such as miRNAs, that act locally or circulate to distant sites to modulate target cell functions. Here, we find that long-term education of breast cancer cells with EVs obtained from breast adipose tissue of women who are overweight or obese (O-EVs) results in increased proliferation. RNA-seq analysis of O-EV-educated cells demonstrates increased expression of genes involved in oxidative phosphorylation, such as ATP synthase and NADH: ubiquinone oxidoreductase. O-EVs increase respiratory complex protein expression, mitochondrial density, and mitochondrial respiration in tumor cells. The mitochondrial complex I inhibitor metformin reverses O-EV-induced cell proliferation. Several miRNAs-miR-155-5p, miR-10a-3p, and miR-30a-3p-which promote mitochondrial respiration and proliferation, are enriched in O-EVs relative to EVs from lean women. O-EV-induced proliferation and mitochondrial activity are associated with stimulation of the Akt/mTOR/P70S6K pathway, and are reversed upon silencing of P70S6K. This study reveals a new facet of the obesity-breast cancer link with human breast adipose tissue-derived EVs causing metabolic reprogramming of breast cancer cells.

Plasma metabolomics profiling of 580 patients from an Early Detection Research Network prostate cancer cohort.

Prostate cancer is the second most common cancer in men and affects 1 in 9 men in the United States. Early screening for prostate cancer often involves monitoring levels of prostate-specific antigen (PSA) and performing digital rectal exams. However, a prostate biopsy is always required for definitive cancer diagnosis. The Early Detection Research Network (EDRN) is a consortium within the National Cancer Institute aimed at improving screening approaches and early detection of cancers. As part of this effort, the Weill Cornell EDRN Prostate Cancer has collected and biobanked specimens from men undergoing a prostate biopsy between 2008 and 2017. In this report, we describe blood metabolomics measurements for a subset of this population. The dataset includes detailed clinical and prospective records for 580 patients who underwent prostate biopsy, 287 of which were subsequentially diagnosed with prostate cancer, combined with profiling of 1,482 metabolites from plasma samples collected at the time of biopsy. We expect this dataset to provide a valuable resource for scientists investigating prostate cancer metabolism.

A multimodal atlas of tumour metabolism reveals the architecture of gene-metabolite covariation.

Tumour metabolism is controlled by coordinated changes in metabolite abundance and gene expression, but simultaneous quantification of metabolites and transcripts in primary tissue is rare. To overcome this limitation and to study gene-metabolite covariation in cancer, we assemble the Cancer Atlas of Metabolic Profiles of metabolomic and transcriptomic data from 988 tumour and control specimens spanning 11 cancer types in published and newly generated datasets. Meta-analysis of the Cancer Atlas of Metabolic Profiles reveals two classes of gene-metabolite covariation that transcend cancer types. The first corresponds to gene-metabolite pairs engaged in direct enzyme-substrate interactions, identifying putative genes controlling metabolite pool sizes. A second class of gene-metabolite covariation represents a small number of hub metabolites, including quinolinate and nicotinamide adenine dinucleotide, which correlate to many genes specifically expressed in immune cell populations. These results provide evidence that gene-metabolite covariation in cellularly heterogeneous tissue arises, in part, from both mechanistic interactions between genes and metabolites, and from remodelling of the bulk metabolome in specific immune microenvironments.

piTracer - Automatic reconstruction of molecular cascades for the identification of synergistic drug targets.

Cancer cells frequently undergo metabolic reprogramming as a mechanism of resistance against chemotherapeutic drugs. Metabolomic profiling provides a direct readout of metabolic changes and can thus be used to identify these tumor escape mechanisms. Here, we introduce piTracer, a computational tool that uses multi-scale molecular networks to identify potential combination therapies from pre- and post-treatment metabolomics data. We first demonstrate piTracer’s core ability to reconstruct cellular cascades by inspecting well-characterized molecular pathways and previously studied associations between genetic variants and metabolite levels. We then apply a new gene ranking algorithm on differential metabolomic profiles from human breast cancer cells after glutaminase inhibition. Four of the automatically identified gene targets were experimentally tested by simultaneous inhibition of the respective targets and glutaminase. Of these combination treatments, two were be confirmed to induce synthetic lethality in the cell line. In summary, piTracer integrates the molecular monitoring of escape mechanisms into comprehensive pathway networks to accelerate drug target identification. The tool is open source and can be accessed at https://github.com/krumsieklab/pitracer .

Breast adipose tissue-derived extracellular vesicles from women with obesity stimulate mitochondrial-induced dysregulated tumor cell metabolism.

Breast adipose tissue is an important contributor to the obesity-breast cancer link. Dysregulated cell metabolism is now an accepted hallmark of cancer. Extracellular vesicles (EVs) are nanosized particles containing selective cargo, such as miRNAs, that act locally or circulate to distant sites to modulate target cell functions. Here, we found that long-term education of breast cancer cells (MCF7, T47D) with EVs from breast adipose tissue of women who are overweight or obese (O-EVs) leads to sustained increased proliferative potential. RNA-Seq of O-EV-educated cells demonstrates increased expression of genes, such as ATP synthase and NADH: ubiquinone oxidoreductase, involved in oxidative phosphorylation. O-EVs increase respiratory complex protein expression, mitochondrial density, and mitochondrial respiration in tumor cells. Mitochondrial complex I inhibitor, metformin, reverses O-EV-induced cell proliferation. Several miRNAs, miR-155-5p, miR-10a-3p, and miR-30a-3p, which promote mitochondrial respiration and proliferation, are enriched in O-EVs relative to EVs from lean women. O-EV-induced proliferation and mitochondrial activity are associated with stimulation of the Akt/mTOR/P70S6K pathway, and are reversed upon silencing of P70S6K. This study reveals a new facet of the obesity-breast cancer link with human breast adipose tissue-derived EVs causing the metabolic reprogramming of ER+ breast cancer cells.

Validation of disease-specific biomarkers for the early detection of bronchopulmonary dysplasia.

OBJECTIVE: To demonstrate and validate the improvement of current risk stratification for bronchopulmonary dysplasia (BPD) early after birth by plasma protein markers (sialic acid-binding Ig-like lectin 14 (SIGLEC-14), basal cell adhesion molecule (BCAM), angiopoietin-like 3 protein (ANGPTL-3)) in extremely premature infants. METHODS AND RESULTS: Proteome screening in first-week-of-life plasma samples of n = 52 preterm infants <32 weeks gestational age (GA) on two proteomic platforms (SomaLogic®, Olink-Proteomics®) confirmed three biomarkers with significant predictive power: BCAM, SIGLEC-14, and ANGPTL-3. We demonstrate high sensitivity (0.92) and specificity (0.86) under consideration of GA, show the proteins' critical contribution to the predictive power of known clinical risk factors, e.g., birth weight and GA, and predicted the duration of mechanical ventilation, oxygen supplementation, as well as neonatal intensive care stay. We confirmed significant predictive power for BPD cases when switching to a clinically applicable method (enzyme-linked immunosorbent assay) in an independent sample set (n = 25, p < 0.001) and demonstrated disease specificity in different cohorts of neonatal and adult lung disease. CONCLUSION: While successfully addressing typical challenges of clinical biomarker studies, we demonstrated the potential of BCAM, SIGLEC-14, and ANGPTL-3 to inform future clinical decision making in the preterm infant at risk for BPD. TRIAL REGISTRATION: Deutsches Register Klinische Studien (DRKS) No. 00004600; https://www.drks.de . IMPACT: The urgent need for biomarkers that enable early decision making and personalized monitoring strategies in preterm infants with BPD is challenged by targeted marker analyses, cohort size, and disease heterogeneity. We demonstrate the potential of the plasma proteins BCAM, SIGLEC-14, and ANGPTL-3 to identify infants with BPD early after birth while improving the predictive power of clinical variables, confirming the robustness toward proteome assays and proving disease specificity. Our comprehensive analysis enables a phase-III clinical trial that allows full implementation of the biomarkers into clinical routine to enable early risk stratification in preterms with BPD.

Microbes Contribute to Chemopreventive Efficacy, Intestinal Tumorigenesis, and the Metabolome.

Bacteria are believed to play an important role in intestinal tumorigenesis and contribute to both gut luminal and circulating metabolites. Celecoxib, a selective cyclooxygenase-2 inhibitor, alters gut bacteria and metabolites in association with suppressing the development of intestinal polyps in mice. The current study sought to evaluate whether celecoxib exerts its chemopreventive effects, in part, through intestinal bacteria and metabolomic alterations. Using ApcMin/+ mice, we demonstrated that treatment with broad-spectrum antibiotics (ABx) reduced abundance of gut bacteria and attenuated the ability of celecoxib to suppress intestinal tumorigenesis. Use of ABx also impaired celecoxib's ability to shift microbial populations and gut luminal and circulating metabolites. Treatment with ABx alone markedly reduced tumor number and size in ApcMin/+ mice, in conjunction with profoundly altering the metabolite profiles of the intestinal lumen and blood. Many of the metabolite changes in the gut and circulation overlapped and included shifts in microbially derived metabolites. To complement these findings in mice, we evaluated the effects of ABx on circulating metabolites in patients with colon cancer. This showed that ABx treatment led to a shift in blood metabolites, including several that were of bacterial origin. Importantly, changes in metabolites in patients given ABx overlapped with alterations found in mice that also received ABx. Taken together, these findings suggest a potential role for bacterial metabolites in mediating both the chemopreventive effects of celecoxib and intestinal tumor growth. PREVENTION RELEVANCE: This study demonstrates novel mechanisms by which chemopreventive agents exert their effects and gut microbiota impact intestinal tumor development. These findings have the potential to lead to improved cancer prevention strategies by modulating microbes and their metabolites.

Mitonuclear genotype remodels the metabolic and microenvironmental landscape of Hürthle cell carcinoma.

Hürthle cell carcinomas (HCCs) display two exceptional genotypes: near-homoplasmic mutation of mitochondrial DNA (mtDNA) and genome-wide loss of heterozygosity (gLOH). To understand the phenotypic consequences of these genetic alterations, we analyzed genomic, metabolomic, and immunophenotypic data of HCC and other thyroid cancers. Both mtDNA mutations and profound depletion of citrate pools are common in HCC and other thyroid malignancies, suggesting that thyroid cancers are broadly equipped to survive tricarboxylic acid cycle impairment, whereas metabolites in the reduced form of NADH-dependent lysine degradation pathway were elevated exclusively in HCC. The presence of gLOH was not associated with metabolic phenotypes but rather with reduced immune infiltration, indicating that gLOH confers a selective advantage partially through immunosuppression. Unsupervised multimodal clustering revealed four clusters of HCC with distinct clinical, metabolomic, and microenvironmental phenotypes but overlapping genotypes. These findings chart the metabolic and microenvironmental landscape of HCC and shed light on the interaction between genotype, metabolism, and the microenvironment in cancer.

Variational autoencoders learn transferrable representations of metabolomics data.

Dimensionality reduction approaches are commonly used for the deconvolution of high-dimensional metabolomics datasets into underlying core metabolic processes. However, current state-of-the-art methods are widely incapable of detecting nonlinearities in metabolomics data. Variational Autoencoders (VAEs) are a deep learning method designed to learn nonlinear latent representations which generalize to unseen data. Here, we trained a VAE on a large-scale metabolomics population cohort of human blood samples consisting of over 4500 individuals. We analyzed the pathway composition of the latent space using a global feature importance score, which demonstrated that latent dimensions represent distinct cellular processes. To demonstrate model generalizability, we generated latent representations of unseen metabolomics datasets on type 2 diabetes, acute myeloid leukemia, and schizophrenia and found significant correlations with clinical patient groups. Notably, the VAE representations showed stronger effects than latent dimensions derived by linear and non-linear principal component analysis. Taken together, we demonstrate that the VAE is a powerful method that learns biologically meaningful, nonlinear, and transferrable latent representations of metabolomics data.

SGI: automatic clinical subgroup identification in omics datasets.

SUMMARY: The 'Subgroup Identification' (SGI) toolbox provides an algorithm to automatically detect clinical subgroups of samples in large-scale omics datasets. It is based on hierarchical clustering trees in combination with a specifically designed association testing and visualization framework that can process an arbitrary number of clinical parameters and outcomes in a systematic fashion. A multi-block extension allows for the simultaneous use of multiple omics datasets on the same samples. In this article, we first describe the functionality of the toolbox and then demonstrate its capabilities through application examples on a type 2 diabetes metabolomics study as well as two copy number variation datasets from The Cancer Genome Atlas. AVAILABILITY AND IMPLEMENTATION: SGI is an open-source package implemented in R. Package source codes and hands-on tutorials are available at https://github.com/krumsieklab/sgi. The QMdiab metabolomics data is included in the package and can be downloaded from https://doi.org/10.6084/m9.figshare.5904022. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Association of circulating cell-free double-stranded DNA and metabolic derangements in idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease with unclear aetiology and poorly understood pathophysiology. Although plasma levels of circulating cell-free DNA (ccf-DNA) and metabolomic changes have been reported in IPF, the associations between ccf-DNA levels and metabolic derangements in lung fibrosis are unclear. Here, we demonstrate that ccf-double-stranded DNA (dsDNA) is increased in patients with IPF with rapid progression of disease compared with slow progressors and healthy controls and that ccf-dsDNA associates with amino acid metabolism, energy metabolism and lipid metabolism pathways in patients with IPF.

The metabolic adaptation evoked by arginine enhances the effect of radiation in brain metastases.

Selected patients with brain metastases (BM) are candidates for radiotherapy. A lactatogenic metabolism, common in BM, has been associated with radioresistance. We demonstrated that BM express nitric oxide (NO) synthase 2 and that administration of its substrate l-arginine decreases tumor lactate in BM patients. In a placebo-controlled trial, we showed that administration of l-arginine before each fraction enhanced the effect of radiation, improving the control of BM. Studies in preclinical models demonstrated that l-arginine radiosensitization is a NO-mediated mechanism secondary to the metabolic adaptation induced in cancer cells. We showed that the decrease in tumor lactate was a consequence of reduced glycolysis that also impacted ATP and NAD+ levels. These effects were associated with NO-dependent inhibition of GAPDH and hyperactivation of PARP upon nitrosative DNA damage. These metabolic changes ultimately impaired the repair of DNA damage induced by radiation in cancer cells while greatly sparing tumor-infiltrating lymphocytes.

Oncogenic HSP90 Facilitates Metabolic Alterations in Aggressive B-cell Lymphomas.

HSP90 is critical for maintenance of the cellular proteostasis. In cancer cells, HSP90 also becomes a nucleating site for the stabilization of multiprotein complexes including signaling pathways and transcription complexes. Here we described the role of this HSP90 form, referred to as oncogenic HSP90, in the regulation of cytosolic metabolic pathways in proliferating B-cell lymphoma cells. Oncogenic HSP90 assisted in the organization of metabolic enzymes into non-membrane-bound functional compartments. Under experimental conditions that conserved cellular proteostasis, oncogenic HSP90 coordinated and sustained multiple metabolic pathways required for energy production and maintenance of cellular biomass as well as for secretion of extracellular metabolites. Conversely, inhibition of oncogenic HSP90, in absence of apparent client protein degradation, decreased the efficiency of MYC-driven metabolic reprogramming. This study reveals that oncogenic HSP90 supports metabolism in B-cell lymphoma cells and patients with diffuse large B-cell lymphoma, providing a novel mechanism of activity for HSP90 inhibitors. SIGNIFICANCE: The oncogenic form of HSP90 organizes and maintains functional multienzymatic metabolic hubs in cancer cells, suggesting the potential of repurposing oncogenic HSP90 selective inhibitors to disrupt metabolism in lymphoma cells.

Diet-induced alteration of intestinal stem cell function underlies obesity and prediabetes in mice.

Excess nutrient uptake and altered hormone secretion in the gut contribute to a systemic energy imbalance, which causes obesity and an increased risk of type 2 diabetes and colorectal cancer. This functional maladaptation is thought to emerge at the level of the intestinal stem cells (ISCs). However, it is not clear how an obesogenic diet affects ISC identity and fate. Here we show that an obesogenic diet induces ISC and progenitor hyperproliferation, enhances ISC differentiation and cell turnover and changes the regional identities of ISCs and enterocytes in mice. Single-cell resolution of the enteroendocrine lineage reveals an increase in progenitors and peptidergic enteroendocrine cell types and a decrease in serotonergic enteroendocrine cell types. Mechanistically, we link increased fatty acid synthesis, Ppar signaling and the Insr-Igf1r-Akt pathway to mucosal changes. This study describes molecular mechanisms of diet-induced intestinal maladaptation that promote obesity and therefore underlie the pathogenesis of the metabolic syndrome and associated complications.

Seasonal Regulation of Metabolism: The Effect of Wintertime Fasting and Autumnal Fattening on Key Central Regulators of Metabolism and the Metabolic Profile of the Raccoon Dog (Nyctereutes Procyonoides).

Investigations into the mechanisms regulating obesity are frantic and novel translational approaches are needed. The raccoon dog (Nyctereutes procyonoides) is a canid species representing a promising model to study metabolic regulation in a species undergoing cycles of seasonal obesity and fasting. To understand the molecular mechanisms of metabolic regulation in seasonal adaptation, we analyzed key central nervous system and peripheral signals regulating food intake and metabolism from raccoon dogs after autumnal fattening and winter fasting. Expressions of neuropeptide Y (NPY), orexin-2 receptor (OX2R), pro-opiomelanocortin (POMC) and leptin receptor (ObRb) were analyzed as examples of orexigenic and anorexigenic signals using qRT-PCR from raccoon dog hypothalamus samples. Plasma metabolic profiles were measured with 1H NMR-spectroscopy and LC-MS. Circulating hormones and cytokines were determined with canine specific antibody assays. Surprisingly, NPY and POMC were not affected by the winter fasting nor autumn fattening and the metabolic profiles showed a remarkable equilibrium, indicating conserved homeostasis. However, OX2R and ObRb expression changes suggested seasonal regulation. Circulating cytokine levels were not increased, demonstrating that the autumn fattening did not induce subacute inflammation. Thus, the raccoon dog developed seasonal regulatory mechanisms to accommodate the autumnal fattening and prolonged fasting making the species unique in coping with the extreme environmental challenges.

The Colorectal Cancer Lipidome: Identification of a Robust Tumor-Specific Lipid Species Signature.

OBJECTIVE: Lipidomic changes were causally linked to metabolic diseases, but the scenario for colorectal cancer (CRC) is less clear. We investigated the CRC lipidome for putative tumor-specific alterations through analysis of 3 independent retrospective patient cohorts from 2 clinical centers, to derive a clinically useful signature. DESIGN: Quantitative comprehensive lipidomic analysis was performed using direct infusion electrospray ionization coupled with tandem mass spectrometry (ESI-MS/MS) and high-resolution mass spectrometry (HR-MS) on matched nondiseased mucosa and tumor tissue in a discovery cohort (n = 106). Results were validated in 2 independent cohorts (n = 28, and n = 20), associated with genomic and clinical data, and lipidomic data from a genetic mouse tumor model (Apc1638N). RESULTS: Significant differences were found between tumor and normal tissue for glycero-, glycerophospho-, and sphingolipids in the discovery cohort. Comparison to the validation collectives unveiled that glycerophospholipids showed high interpatient variation and were strongly affected by preanalytical conditions, whereas glycero- and sphingolipids appeared more robust. Signatures of sphingomyelin and triacylglycerol (TG) species significantly differentiated cancerous from nondiseased tissue in both validation studies. Moreover, lipogenic enzymes were significantly up-regulated in CRC, and FASN gene expression was prognostically detrimental. The TG profile was significantly associated with postoperative disease-free survival and lymphovascular invasion, and was essentially conserved in murine digestive cancer, but not associated with microsatellite status, KRAS or BRAF mutations, or T-cell infiltration. CONCLUSION: Analysis of the CRC lipidome revealed a robust TG-species signature with prognostic potential. A better understanding of the cancer-associated glycerolipid and sphingolipid metabolism may lead to novel therapeutic strategies.

Exogenous and Endogenous Sources of Serine Contribute to Colon Cancer Metabolism, Growth, and Resistance to 5-Fluorouracil.

Serine is a nonessential amino acid generated by the sequential actions of phosphoglycerate dehydrogenase (PHGDH), phosphoserine aminotransferase (PSAT1), and phosphoserine phosphatase (PSPH). Increased serine biosynthesis occurs in several cancers and supports tumor growth. In addition, cancer cells can harness exogenous serine to enhance their metabolism and proliferation. Here we tested the relative contributions of exogenous and endogenous sources of serine on the biology of colorectal cancer. In murine tumors, Apc status was identified as a determinant of the expression of genes controlling serine synthesis. In patient samples, PSAT1 was overexpressed in both colorectal adenomas and adenocarcinomas. Combining genetic deletion of PSAT1 with exogenous serine deprivation maximally suppressed the proliferation of colorectal cancer cells and induced profound metabolic defects including diminished nucleotide production. Inhibition of serine synthesis enhanced the transcriptional changes following exogenous serine removal as well as alterations associated with DNA damage. Both loss of PSAT1 and removal of serine from the diet were necessary to suppress colorectal cancer xenograft growth and enhance the antitumor activity of 5-fluorouracil (5-FU). Restricting endogenous and exogenous serine in vitro augmented 5-FU-induced cell death, DNA damage, and metabolic perturbations, likely accounting for the observed antitumor effect. Collectively, our results suggest that both endogenous and exogenous sources of serine contribute to colorectal cancer growth and resistance to 5-FU. SIGNIFICANCE: These findings provide insights into the metabolic requirements of colorectal cancer and reveal a novel approach for its treatment. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/81/9/2275/F1.large.jpg.

Dynamic modelling of an ACADS genotype in fatty acid oxidation - Application of cellular models for the analysis of common genetic variants.

BACKGROUND: Genome-wide association studies of common diseases or metabolite quantitative traits often identify common variants of small effect size, which may contribute to phenotypes by modulation of gene expression. Thus, there is growing demand for cellular models enabling to assess the impact of gene regulatory variants with moderate effects on gene expression. Mitochondrial fatty acid oxidation is an important energy metabolism pathway. Common noncoding acyl-CoA dehydrogenase short chain (ACADS) gene variants are associated with plasma C4-acylcarnitine levels and allele-specific modulation of ACADS expression may contribute to the observed phenotype. METHODS AND FINDINGS: We assessed ACADS expression and intracellular acylcarnitine levels in human lymphoblastoid cell lines (LCL) genotyped for a common ACADS variant associated with plasma C4-acylcarnitine and found a significant genotype-dependent decrease of ACADS mRNA and protein. Next, we modelled gradual decrease of ACADS expression using a tetracycline-regulated shRNA-knockdown of ACADS in Huh7 hepatocytes, a cell line with high fatty acid oxidation-(FAO)-capacity. Assessing acylcarnitine flux in both models, we found increased C4-acylcarnitine levels with decreased ACADS expression levels. Moreover, assessing time-dependent changes of acylcarnitine levels in shRNA-hepatocytes with altered ACADS expression levels revealed an unexpected effect on long- and medium-chain fatty acid intermediates. CONCLUSIONS: Both, genotyped LCL and regulated shRNA-knockdown are valuable tools to model moderate, gradual gene-regulatory effects of common variants on cellular phenotypes. Decreasing ACADS expression levels modulate short and surprisingly also long/medium chain acylcarnitines, and may contribute to increased plasma acylcarnitine levels.